You can evaluate all risk factors with our solution: data from natural disasters (NatCat) such as floods, hail, storm, fire or earthquake risk or man-made catastrophes (ManMadeCat) such as crime, accidents, terrorism, pandemics etc.
Visualizing and analysing risks on maps, directing customers to the right partners in the event of accident, claims plausibility check, policy risk accumulation analysis, loss analysis and displaying risk layers for many more use cases.
Solvency 2 regulations require insurance companies to analyze and report portfolio risk accumulation to government. In collaboration with experts we have created a maps based, simple to use system to provide these analysis and reports. Location data can be uploaded and geocoded, displayed on maps together with risk layer information and scenarios can be calculated. The results can easily be exported to a report or as spreadsheet for further workflow. No programming skills or deep GIS knowledge is necessary.
The base system contains risk layers for the most common perils and scenarios, depending on our customers needs. Upon request additional layers and scenarios can be added. The tool is running in Google Cloud Platform, but can also be installed on premises.
For everyday business of underwriters and risk engineers our system can be used for importing and analyzing location data on any available risk factor. This semi automated risk analysis system allows to analyze property and business risk as well as transportation of goods risk.
This way our customers save up to 90% time for analyzing their portfolios using remote sensing, as the product can also be integrated with existing underwriting and offer calculation systems.
The g-Xperts system is highly scalable and very flexible when it come to integration of in house data, third party data (eg. re-insurance or governmental data) or connecting to existing systems as a stand alone add on.
We provide semi-automatic plausibility checks for your personal damage management. Information on risk areas, weather data, storm or flood warnings, police reports or even tweets and any other internal and external information can thus be used by damage analysts in a centralised manner.